Using an autoscaling policy with multiple signals

When you create an autoscaling policy with multiple signals, the autoscaler scales based on the signal that provides the largest number of virtual machine (VM) instances in the managed instance group (MIG). This ensures that there are always enough VMs to handle your application workloads and lets you scale applications with multiple possible bottlenecks.

To learn more about the different types of autoscaling signals, see Autoscaling policy.

Before you begin

How autoscaler handles multiple signals

An autoscaler handles multiple signals by calculating the recommended number of VMs for each signal and then picking the signal that results in the largest number of VMs in the MIG.

An autoscaler can handle one signal per metric type except in the case of Cloud Monitoring metrics and scaling schedules. You can choose up to 5 autoscaling signals for Cloud Monitoring metrics and create up to 128 schedules per MIG. For example, you can create an autoscaler that uses up to 1 CPU utilization signal, up to 1 load balancing signal, up to 5 custom metric signals, and up to 128 scaling schedules.

In this example, suppose the autoscaler measures the following average utilization values for a MIG that contains 10 VMs at the time of measurement:

Using the preceding values, the autoscaler calculates the recommended number of VMs based on each signal:

The autoscaler picks the signal that results in the largest number of VMs in the MIG and sets the MIG's recommended size to that value. In this case, the autoscaler resizes the MIG to 15 VMs if the second schedule is currently active or to 14 VMs otherwise.

Create an autoscaler with multiple signals

Creating an autoscaler with multiple signals is slightly different depending on whether you are using the Google Cloud console, gcloud CLI, or REST.

Permissions required for this task

To perform this task, you must have the following permissions:

To create a new autoscaler for an existing MIG:
- compute.autoscalers.create on the project
- compute.instanceGroupManagers.use on the MIG
To edit an existing autoscaler:
- compute.autoscalers.update on the project

Console

In the Google Cloud console, go to the Instance groups page.

Go to Instance groups
Click the name of a MIG from the list.
Click Edit.
Click Group size & autoscaling to expand the section.
In the Autoscaling mode list, make sure that On: add and remove instances to the group is selected.
In the Minimum number of instances field, enter the minimum number of VMs that you want for this MIG. The minimum size of this MIG is always maintained regardless of its autoscaling signals.
In the Maximum number of instances field, enter the maximum number of VMs that you want for this MIG. The maximum size of this MIG is never exceeded regardless of the recommended size generated by its autoscaling signals.
For each metric-based autoscaling signal that you want to add, click Add a signal.
- To create an autoscaling signal based on average CPU utilization, in the Signal type list, select CPU utilization. Then, enter a Target CPU utilization and click Done. For more information, see Scaling based on CPU utilization.
- To create an autoscaling signal based on HTTP load balancing serving capacity, in the Signal type list, select HTTP load balancing utilization. Then, enter a Target HTTP load balancing utilization and click Done. For more information, see Scaling based on load balancing serving capacity.
- To create an autoscaling signal based on Cloud Monitoring metrics, in the Signal type list, select Cloud Monitoring metric. Then, complete the remaining fields and click Done. For more information, see Scaling based on Cloud Monitoring metrics.
For each schedule-based autoscaling signal that you want to add, in the Autoscaling schedules section, click Manage.
1. Click Create schedule.
2. In the Create scaling schedule pane, complete the required fields, and then click Save.
3. In the Scaling schedules pane, click Done.
For more information, see Scaling based on schedules.
In the Initialization period section, enter the number of seconds that your application needs to initialize. This period lets your VMs finish initializing before the autoscaler considers its usage data reliable. For more information, see Initialization period.
Optional: to enable scale-in controls, in the Scale-in controls section, select the Enable scale-in controls checkbox. For more information, see scale-in controls
Click Save.

gcloud

To create an autoscaler with multiple signals, use the set-autoscaling command. Pass in multiple signal specifications using their respective command-line flags.

For example, the following command creates an autoscaler that uses CPU utilization, load balancing serving capacity, two custom metrics, and one scaling schedule. The --max-num-replicas and --min-num-replicas flags restrict how big or small the MIG can get.

gcloud compute instance-groups managed set-autoscaling MIG_NAME \
   --target-cpu-utilization=0.8 \
   --target-load-balancing-utilization=0.6 \
   --custom-metric-utilization metric=PATH_TO_CUSTOM_METRIC_1,utilization-target=1000.0,utilization-target-type=GAUGE \
   --custom-metric-utilization metric=PATH_TO_CUSTOM_METRIC_2,utilization-target=2000.0,utilization-target-type=DELTA_PER_SECOND \
   --set-schedule=workday-capacity \
   --schedule-cron="30 8 * * Mon-Fri" \
   --schedule-duration-sec=30600 \
   --schedule-min-required-replicas=10 \
   --schedule-description="Have at least 10 VMs every Monday through Friday from 8:30 AM to 5 PM UTC" \
   --min-num-replicas=1 \
   --max-num-replicas=50

Replace the following:

MIG_NAME: the name of a MIG.
PATH_TO_CUSTOM_METRIC_1 and PATH_TO_CUSTOM_METRIC_2: Optional: the paths to custom metrics with a format similar to custom.cloudmonitoring.googleapis.com/path/to/metric1 and custom.cloudmonitoring.googleapis.com/path/to/metric2. For more information, see Custom metrics.

With the exception of the custom metric flags, you can only pass in one flag maximum for each metric type per gcloud command. For custom metrics, you can provide multiple custom metrics in a single command by repeating the --custom-metric-utilization flag.

For more information about how to configure the flags for each type of autoscaling signal, see the following pages:

REST

To create an autoscaler, use the autoscalers.insert method for a zonal MIG or the regionAutoscalers.insert method for a regional MIG.

For example, the following request creates an autoscaler that uses CPU utilization, load balancing serving capacity, two custom metrics, and two scaling schedules. The maxNumReplicas and minNumReplicas fields restrict how big or small the MIG can get.

POST https://compute.googleapis.com/compute/v1/projects/PROJECT/zones/ZONE/autoscalers

{
  "autoscalingPolicy" : {
    "cpuUtilization":{
      "utilizationTarget": 0.8
    },
    "loadBalancingUtilization":{
      "utilizationTarget": 0.6
    },
    "customMetricUtilizations":[
      {
        "metric": "PATH_TO_CUSTOM_METRIC_1",
        "utilizationTarget": 1000,
        "utilizationTargetType":"GAUGE"
      },
      {
        "metric": "PATH_TO_CUSTOM_METRIC_2",
        "utilizationTarget": 2000,
        "utilizationTargetType": "DELTA_PER_SECOND"
      }
    ],
    "scalingSchedules": {
      "workday-capacity": {
        "minRequiredReplicas": 10,
        "schedule": "30 8 * * Mon-Fri",
        "durationSec": 30600,
        "description": "Have at least 10 VMs every Monday through Friday from 8:30 AM to 5 PM UTC"
      },
      "january-30-2030-schedule": {
        "minRequiredReplicas": 30,
        "schedule": "0 0 30 1 * 2030",
        "timeZone": "America/New_York",
        "durationSec": 86400,
        "description": "Schedule a minimum of 30 VMs all day for January 30, 2030"
      }
    },
    "maxNumReplicas": 50,
    "minNumReplicas": 1
  },
  "target": "https://www.googleapis.com/compute/v1/projects/myproject/zones/us-central1-a/instanceGroupManagers/MIG_NAME",
  "name": "MIG_NAME"
}

Replace the following:

PROJECT: your project id.
ZONE: the zone where your MIG is located.
MIG_NAME: the name of a MIG.
PATH_TO_CUSTOM_METRIC_1 and PATH_TO_CUSTOM_METRIC_2: Optional: the paths to custom metrics with a format similar to custom.cloudmonitoring.googleapis.com/path/to/metric1 and custom.cloudmonitoring.googleapis.com/path/to/metric2. For more information, see Custom metrics.

As shown in this example, you can provide multiple custom metrics and scaling schedules in the same request.

For more information about how to configure the fields for each type of autoscaling signal, see the following pages:

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2026-06-09 UTC.

Using an autoscaling policy with multiple signals Stay organized with collections Save and categorize content based on your preferences.

Before you begin

Console

gcloud

REST

How autoscaler handles multiple signals

Create an autoscaler with multiple signals

Permissions required for this task

Console

gcloud

REST

Using an autoscaling policy with multiple signals